This paper shows the use of new discrete event based numerical integration methods applied to the simulation of sliding mode control systems. These methods have many advantages in the simulation of general discontinuous and hybrid systems. In this case, a comparative study is performed showing that the simulation time can be significatively reduced with respect to any method implemented in Simu...

This paper presents a multivariable self-tuning control based on the idea of discrete-time sliding mode. The previous stability proof based on the Lyapunov function is corrected in the MIMO framework that plant input and output have the same dimension. The performance of the proposed method is evaluated in the simulation environment designed for MBD (model based development) of automotive syste...

A Fuzzy Power System Stabiliser (FPSS) design using discrete inputs is presented. The FPSS basically utilises only one measurable plant signal as input, namely, the generator speed. The speed signal is discretised resulting in three inputs to the FPSS. A simplified power system represented by a single generator transmitting power to the infinite bus is considered for investigations. The system ...

In this paper, we present a new sliding mode controller for a class of unknown nonlinear discrete-time systems. We make the following two modifications: 1) The neural identifier which is used to estimate the unknown nonlinear system, applies new learning algorithms. The stability and non-zero properties are proved by dead-zone and projection technique. 2) We propose a new sliding surface and gi...

In this paper we present a new algorithm for discrete sliding mode control of linear multivariable systems using fast output sampling feedback. Here we make use of a single switching surface regardless of the number of inputs. The main contribution of this work is that instead of using the system states, the output samples are used for designing the controller. Numerical example demonstrates th...

The problem of identification of uncertain nonlinear systems using feedforward neural networks is investigated. The weights of the neural identifier are updated on-line by a discrete-time learning algorithm based on the sliding mode control technique, which is well known with its robustness to uncertainties. The learning parameters are adjusted to force the error between the actual and desired ...

In this paper we consider the modelling and control of discrete event systems using switching max-plus-linear systems. In switching max-plus-linear systems we can switch between different modes of operation. In each mode the discrete event system is described by a max-plus-linear state equation with different systemmatrices for each mode. The switching allows us to change the structure of the s...

A method to find discrete solitons in nonlinear lattices is introduced. Using nonlinear optical waveguide arrays as a prototype application, both stationary and traveling-wave solitons are investigated. In the limit of small wave velocity, a fully discrete perturbative analysis yields formulas for the mode shapes and velocity.

In this paper, a novel technique of second order recursive reaching law based sliding mode control for a discrete-time system is presented. The proposed second order recurrence dictates the dynamics of sliding function using its two past terms. The synthesized control input utilises two past control inputs and results in better continuity in discrete-time, known as (p,q)-continuity.

Combination of sliding-mode control and an AI block based on fuzzy logic is introduced. This hybrid control structure provides very good control performance and robustness of control loops. Based on the Lyapunov’s direct method, the sliding mode control is designed to guarantee the stability and good tracking performance of controlled systems. The fuzzy logic block is designed to mimic the beha...